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Virtual team meetings are increasingly supported with advanced technology. This study investigates the extent to which Al-enabled speech technology can be useful for global virtual teams (GVT). A survey was conducted in GVTs in 2020 and 2021, when people's lives were primarily dominated by the pandemic. A transcription software was used to support the collaboration. A total of 530 survey responses were analyzed using a structured approach- qualitative content analysis. The data was structured using the SWOT framework that aimed at comprehensively answering the research question "To what extent is the use of Al-supported speech technology in GVTs useful?". Al-generated transcripts are helping to overcome language and time zone barriers in GVT. Yet, they also cause misunderstandings and impact openness of communication. Further results and implications for GVT are discussed.
In this research, we discuss the past and current trends in defining poverty to look at the topic from different perspectives and to provide an outline of future work that we aim to complete the picture on the qualitative and quantitative side. For this purpose, our focus here is to evaluate the diversity of definitions and to emphasize how important it is to combine subjective and objective approaches for practical policy analysis. As a first step of our future work, we also present the pilot study results to assess the results comparatively in the EU states and Türkiye.
The impulse to think about process-induced social networks (in short: process networks) comes from the discipline of “Process Mining” (e.g. van der Aalst et al. 2005). The relevant literature refers to an "organizational view" or "organizational mining" in process mining.
In essence, process mining is about creating a time-logical chain of related tasks from automatically logged user activities on a computer. In this way, real processes can be mapped and analyzed as models. As a "by-product", task-related social networks are created between the process participants through the predecessor/successor relationships in the workflow.
However, it should be noted and criticized that process mining research neglects the potential of social network analysis. The extensive findings of classical network research are not taken up further. An organizational and social scientific deepening of the data-driven preliminary work is missing in this discipline. Process mining, which tends to be mathematical and technical, has not yet developed the ambition to ally itself with empirical organizational and social research.
This working paper tries to counteract this. It presents a first, social science-based approach to theoretically grounding process networks.
Will ChatGPT revolutionize accounting?
The Benefits of Artificial Intelligence (AI) in Accounting
(2023)
It's an experiment! This paper explores how ChatGPT can be used in accounting and reporting to au-tomate routine tasks, increase efficiency, and better understand financial data. The creation of the paper itself was done with the help of ChatGPT, i.e., significant parts of this text were created by the AI and then edited and completed by the author in terms of content and language. On the one hand, this is intended to show the potential of the application in practice and to make it clear that dealing with the tools of AI will be indispensable in the future, but on the other hand, the risks and concerns are also addressed.
Varying thermal stresses influence significantly the time to failure of electric components as used, for instance, in automotive devices. For applications as autonomous driving a high reliability has to be guaranteed.
In this article we discuss how to combine probability distributions for failure. Discrete and continuous changes of the probability distribution in time are both considered. It turns out that the temporal order of the distributions, corresponding to the succession of stresses in applications, is essential.
The latter observation restricts the general applicability of the widely used temperature collectives where only the total time of a temperature stress is considered neglecting the order of the stresses.
An application of our results are thermal overstress tests on electric components. We may explain yet not well understood measurements for automotive electric cables.
We report from an ongoing process to develop a thermal conceptual assessment that covers the essential concepts of first-year thermodynamics to be administered to engineering students. The goal is to develop a measurement instrument in order to investigate students’ pre-knowledge as well as the influence of teaching and learning settings. The assessment builds on known misconceptions and concept questions described in the literature. The original items have been modified significantly in the current version 3 of the test in order to create single-choice questions with four distracters each that address frequent misconceptions from student answers in a systematic way. The working process to create these distracters is described exemplarily.
Background
Pharmaceutical expenditure grow strongly in most health care systems. Especially high prices of new drugs are perceived to be driver of growth which might threaten the sustainability of financing drugs.
Objective
The study aims to analyse a) whether German health policies can achieve sustainable growth of pharmaceutical expenditure, and b) which therapeutic groups fasten and slow pharmaceutical growth based on price and/or volume effects.
Methods
Annual growth rates of pharmaceutical expenditure in the German social health insurance (SHI) between 2006 and 2018 are compared with indicators reflecting the ability to pay. Annual growth rate in therapeutic subgroups are analysed with respects to volume and price developments.
Results
Without policies to control pharmaceutical spending, annual growth rates are significantly higher than the growths of indicators of ability to pay. After accounting for the savings from health policy
measures, net pharmaceutical expenditure does not grow significantly faster than ability to pay. Policies mainly targeting generic drugs achieve threefold savings compared with policies targeting at patent-protected drugs, although the latter account for more than halve of the expenditure. A limited number of therapeutic subgroups with new drugs grow significantly faster than average expenditure, but this growths is counterbalanced by subgroups which in the end of their innovation cycle and a huge proportion of generic drugs.
Conclusion
The growths of net drug expenditure in the German SHI does not threaten the sustainability of financing health expenditure based on comprehensive policy measures and innovation cycle effects. Generics do contribute savings to a larger extent.
Key points for decision makers:
• Germany efficiently uses a comprehensive set of health policies to control drug expenditure in the social health insurance with limited impact on reimbursement.
• Net drug expenditure grow on annual rates which correlate to ability to pay and thus do not threaten sustainability of health care financing.
• Natural progress of innovation cycles together with targeted policies on patent-protected as well as generic drugs counterbalance exaggerated growth in areas with a high degree of innovation.
• Policies targeted mainly on generic drugs yield threefold savings compared with policies targeting on patent-protected drugs. This imbalance should be considered in potential refinements of drug policies.
Technological advancement and digitization have become more and more important in recent years. This is particularly true for credit institutions. The core banking systems used for internal processes are therefore subject to increasing digital change. In many banks, outdated IT systems are still in use, which often lack the basic functionalities that are essential for innovations.
In order to achieve a sufficient functionality of the information technology in the company, core banking systems are implemented, which achieve the mapping of almost all bank-specific processes. In addition, so-called software robots are used to automate standard processes with increasing frequency. Due to the lack of standard products in previous years, there is an abundance of in-house developments. While self-developed systems dominate in the European as well as North and South American markets, earlier in-house developments in the German-speaking countries have mainly been replaced by standardized core banking systems.
The introduction of standard ERP systems poses a major challenge for financial institutions. Not only does the implementation effort in terms of financial resources and working time play an important role, but also the ongoing expenses for maintenance and further development. These investments not only secure and promote the ability to innovate in the age of digitization, but also create an asset in the company. The evaluation for the accounting representation is an increasing challenge due to the steadily increasing complexity of information processing technologies. Questions arise regarding the access assessment, the follow-up assessment and the handling of previous systems. In the following, accounting according to the international accounting standards for the implementation of the ERP system SAP S/4HANA in credit institutions is shown. The procedure and the results are not limited to banks, but can be applied analogously to many industries.
When monitoring the energy performance of buildings, it may be of interest to identify the occupation periods of people in the room due to their possible impact on the energy balance. In order to be able to carry out a comprehensive energy assessment of the system and building, it is necessary to be able to classify user influence during the evaluation. This thesis investigates how the presence of people in a room can be determined cost-effectively and with little additional effort. The aim is to determine which sensors of a room control system provide sufficiently reliable data. The presence of 1-2 persons was examined on a test facility of the Technical University Rosenheim. The air-, mean radiation- and surface-temperatures, the air humidity as well as the CO2 and VOC concentrations were measured. For the analysis, a method of supervised machine and statistical learning, random forest, is used. The smallest model error detected in predicting the presence of 1 or 2 persons from CO2 sensor data is 1.43%. The error rates are low for all tested models if time-dynamic effects are used as predictors and the data is processed in a so-called time period form. Additionally, the ways in which this data should ideally be made available for future measurements and processed to facilitate analysis with machine and statistical learning techniques have been investigated. A further goal is to apply the models developed on measurement series in laboratory environments to real rooms and to assess the transferability of these models.
In this work we investigate students’ thinking about and difficulties with incompressible, steady pipe flow. There is substantial evidence that students have difficulty applying and prioritizing the two basic principles of mass conservation (i.e., the continuity equation) and energy conservation (i.e., Bernoulli’s equation). When distracted by questions which involve gravity students based their answers on ill-supported assumptions about local pressures. The predominant arguments use a simplified Bernoulli equation, descriptive arguments or analogies to single-particle motion. Based on these results, an instructional intervention is developed that seems to address the observed difficulties.